Method and Apparatus Pertaining to the Identification of Physical-Local Discrepancies in Statistics-Based RFID-Tag Information

ABSTRACT

These teachings are suitable for use in conjunction with a process having access to both coverage information that maps the coverage area for each of a plurality of RFID-tag readers to physical locations within a given monitored facility and historical-read information for a population of RFID tags, and that uses that historical-read information and that coverage information to automatically determine the physical location of RFID tags. In particular, these teachings generally provide for accessing supplemental information regarding physical locations for at least some of those RFID tags and then comparing the automatically-determined physical location information with the supplemental information to thereby identify physical-location discrepancies. By one approach those physical-location discrepancies are used to adjust the automated process by which the automatically-determined physical location information is automatically determined to thereby improve accuracy of the automated process.

RELATED APPLICATION(S)

This is a continuation of U.S. patent application Ser. No. 13/826,442,Filed Mar. 14, 2013, entitled METHOD AND APPARATUS PERTAINING TO THEIDENTIFICATION OF PHYSICAL-LOCAL DISCREPANCIES IN STATISTICS-BASEDRFID-TAG INFORMATION, which is incorporated by reference in its entiretyherein. entirety.

TECHNICAL FIELD

This disclosure relates generally to the use of radio-frequencyidentification (RFID) tags.

BACKGROUND

RFID tags are known in the art. These so-called tags often assume theform factor of a label or a literal “tag” but are also sometimesintegrated with a host article and/or its packaging. RFID tags typicallycomprise an integrated circuit and one or more antennas. The integratedcircuit typically carries out a variety of functions includingmodulating and demodulating radio frequency signals, data storage, anddata processing. Some integrated circuits are active or self-powered (inwhole or in part) while others are passive, being completely dependentupon an external power source (such as an RFID tag reader) to supporttheir occasional functionality.

There are proposals to utilize RFID tags to uniquely identify individualitems. The Electronic Product Code (EPC) as managed by EPCGlobal, Inc.represents one such effort in these regards. EPC-based RFID tags eachhave a unique (within the EPC universe) serial number to therebyuniquely identify each tag and, by association, each item associated ona one-for-one basis with such tags. (The corresponding document entitledEPC Radio-Frequency Identity Protocols Class-1 Generation-2 UHF RFIDProtocol for Communications at 860 MHz-960 MHz Version 1.0.9 is herebyfully incorporated herein by this reference.)

In some cases a system designer will seek to provide more-or-lessubiquitous coverage through a given facility (such as a retail store)and thereby have the theoretical ability to read an RFID tag regardlessof where that tag might be located within the facility. By one approach,for example, a plurality of RFID-tag readers may hang suspended from theceiling of the monitored facility. Examples in such regards can befound, for example, in U.S. patent application Ser. No. 12/900,191,entitled METHOD AND APPARATUS PERTAINING TO RFID TAG READER ANTENNAARRAY, the contents of which are also fully incorporated herein by thisreference.

Unfortunately, while it can be very helpful to read a particular RFIDtag to thereby gain its tag-specific information, to a very large extentthe system can remain quite effectively blind to the physical locationof that RFID tag within the monitored facility (as the RFID tag itselfhas no such physical-location information to impart). This lack ofuseful information regarding physical location becomes even more acutewhen taking into account the fact that coverage areas for differentRFID-tag readers can and will overlap.

BRIEF DESCRIPTION OF THE DRAWINGS

The above needs are at least partially met through provision of themethod and apparatus pertaining to the identification of physical-localdiscrepancies in statistics-based RFID-tag information described in thefollowing detailed description, particularly when studied in conjunctionwith the drawings, wherein:

FIG. 1 comprises a flow diagram as configured in accordance with variousembodiments of the invention;

FIG. 2 comprises a block diagram as configured in accordance withvarious embodiments of the invention;

FIG. 3 comprises a top plan schematic view as configured in accordancewith various embodiments of the invention;

FIG. 4 comprises a top plan schematic view as configured in accordancewith various embodiments of the invention;

FIG. 5 comprises a top plan schematic view as configured in accordancewith various embodiments of the invention; and

FIG. 6 comprises a flow diagram as configured in accordance with variousembodiments of the invention.

Elements in the figures are illustrated for simplicity and clarity andhave not necessarily been drawn to scale. For example, the dimensionsand/or relative positioning of some of the elements in the figures maybe exaggerated relative to other elements to help to improveunderstanding of various embodiments of the present invention. Also,common but well-understood elements that are useful or necessary in acommercially feasible embodiment are often not depicted in order tofacilitate a less obstructed view of these various embodiments of thepresent invention. Certain actions and/or steps may be described ordepicted in a particular order of occurrence while those skilled in theart will understand that such specificity with respect to sequence isnot actually required. The terms and expressions used herein have theordinary technical meaning as is accorded to such terms and expressionsby persons skilled in the technical field as set forth above exceptwhere different specific meanings have otherwise been set forth herein.

DETAILED DESCRIPTION

Generally speaking, these teachings are suitable for use in conjunctionwith a process having access to both coverage information that maps thecoverage area for each of a plurality of RFID-tag readers to physicallocations within a given monitored facility and historical-readinformation for a population of RFID tags, and that uses thathistorical-read information and that coverage information toautomatically determine the physical location of RFID tags. Inparticular, these teachings generally provide for accessing supplementalinformation regarding physical locations for at least some of those RFIDtags and then comparing the automatically-determined physical locationinformation with the supplemental information to thereby identifyphysical-location discrepancies. By one approach those physical-locationdiscrepancies are used to adjust the automated process by which theautomatically-determined physical location information is automaticallydetermined to thereby improve accuracy of the automated process.

These teachings are highly flexible in practice and will accommodate avariety of approaches as regard the foregoing actions. For example, theaforementioned supplemental information can comprise one or more of afloor plan-based planogram for at least part of the given facility,information gleaned from handheld-based RFID-tag readers, informationgleaned from handheld-based optical-code readers, information gleanedfrom video analytics, and/or information received through locationreviewed from customers of the facility, to note but a few possibilitiesin these regards.

These teachings can be particularly helpful in application settings thatinvolve tens of thousands (or even hundreds of thousands) of RFID tagswithin a given monitored facility. In particular, these teachings can bereadily leveraged in a variety of ways to compensate for an inability toread all RFID tags all the time and also to help leverage as well asdisambiguate location information that can arise from applicationsettings that employ a plurality of RFID-tag readers having at leastpartially overlapping coverage areas. Those skilled in the art willfurther appreciate that improving a statistics-based process forcorrelating RFID tags with a physical location per these teachings canoffer a considerable increase as regards the reliability of physicallocation conclusions that are based upon RFID-tag reads.

These and other benefits may become clearer upon making a thoroughreview and study of the following detailed description. To begin, thisdescription will first present an example of a statistics-based approachto automatically correlating individual RFID tags with correspondingphysical locations within a given monitored facility. Referring now tothe drawings, and in particular to FIG. 1, for the sake of anillustrative example this description will presume that a controlcircuit carries out the described activities and that this controlcircuit has access to coverage information 101 that maps coverage foreach of a plurality of RFID-tag readers to physical locations within agiven monitored facility.

Referring to FIG. 2, such a control circuit 201 can comprise afixed-purpose hard-wired platform or can comprise a partially or whollyprogrammable platform. These architectural options are well known andunderstood in the art and require no further description here. Thiscontrol circuit 201 is configured (for example, by using correspondingprogramming as will be well understood by those skilled in the art) tocarry out one or more of the steps, actions, and/or functions describedherein.

The control circuit 201 in this example operably couples to a memory202. The memory 202 may be integral to the control circuit 201 or can bephysically discrete (in whole or in part) from the control circuit 201as desired. This memory 202 can also be local with respect to thecontrol circuit 201 (where, for example, both share a common circuitboard, chassis, power supply, and/or housing) or can be partially orwholly remote with respect to the control circuit 201 (where, forexample, the memory 202 is physically located in another facility,metropolitan area, or even country as compared to the control circuit201).

This memory 202 can serve, for example, to store the aforementionedcoverage information 101. This memory 202 can also serve tonon-transitorily store the computer instructions that, when executed bythe control circuit 201, cause the control circuit 201 to behave asdescribed herein. (As used herein, this reference to “non-transitorily”will be understood to refer to a non-ephemeral state for the storedcontents (and hence excludes when the stored contents merely constitutesignals or waves) rather than volatility of the storage media itself andhence includes both non-volatile memory (such as read-only memory (ROM)as well as volatile memory (such as an erasable programmable read-onlymemory (EPROM).)

In this example the control circuit 201 also operably couples to aplurality of RFID-tag readers 203 that are dispersed about thecorresponding monitored facility. A variety of approaches are known inthe art in these regards. It will be presumed here that at least some ofthe RFID-tag readers 203 are mounted to or are otherwise suspended fromthe ceiling of the facility and that at least some of the RFID-tagreaders each have a plurality of reader antennas and/or include asteerable phased antenna array.

In a typical application setting the coverage area for each suchRFID-tag reader 203 is likely to at least partially overlap with thecoverage area of at least one other RFID-tag reader 203. FIG. 3 presentsa simplified illustrative example in these regards. In this examplethere are four RFID-tag readers (denoted by reference numerals 203-1through 203-4) that are spaced apart from one another and that each havea corresponding coverage area (denoted by reference numerals 301 through304).

This reference to “coverage area” will be understood to refer to theeffective reading coverage area engendered by a particular antenna;i.e., the three-dimensional volume within which the radiatedradio-frequency energy is, at least for the most part, of sufficientmagnitude to power up an ordinary RFID tag that is used at the facility.It will be understood that this power level will not be consistentthroughout a given coverage area (for example, the power level at onearea within the coverage area may be less than other areas but stillsufficient in and of itself to power up an RFID tag). For manyapplication settings, a suitable power level will be −15 dbm and above.

It will also be understood that the effective coverage area can itselfinclude not only hot spots of higher energy but also nulls where thelocal energy level is too low to power an RFID tag as described. Nullsand hot spots are the result of the radio-frequency energy reflectingoff various surfaces and constructively interfering (hence producing hotspots) or destructively interfering (hence producing nulls). A furthernuance is that such nulls and hot spots can alternate from one wavelength to another. The presence of such nulls within such a volume shallbe understood to not alter a fair characterization of such a volume ascomprising an effective “coverage area” for a given RFID-tag reader 203.

As illustrated in FIG. 3, coverage areas for different RFID-tag readers203 can occur and vary in any of a variety of ways. The area denoted byreference numeral 305 as comprises a part of the coverage area 302 forthe RFID-tag reader denoted by reference numeral 203-2 only receivesenergy from that one RFID-tag reader 203-2. The area denoted byreference numeral 306, however, represents overlap between two differentcoverage areas 302 and 303 as correspond to two different RFID-tagreaders 203-2 and 203-3. And the area denoted by reference numeral 307represents overlap between all four coverage areas 301 through 304.

The present teachings presume an a priori understanding, at least tosome useful degree, of the coverage areas as apply with respect to agiven monitored facility. This understanding includes an understandingof the location of the RFID-tag readers 203 within the facility and thegeneral metes and bounds of the three-dimensional coverage areas ascorrespond to each such RFID-tag reader 203. If desired, suchinformation can be developed using an empirical approach that providesfor taking readings at various locations within the facility to therebydetermine these boundaries and volumes. By another approach, in lieu ofthe foregoing or in combination therewith, such information may bedeveloped or refined over time and during ordinary use of the RFIDsystem when and as appropriate.

As noted earlier, a given RFID-tag reader 203 can have a plurality ofantennas and/or can include a steerable phased antenna array. In eithercase the coverage area for a given RFID-tag reader 203 can be furthersubdivided as function of those various antennas (or sectors). FIG. 4presents, for example, a coverage area 401 for an RFID-tag reader 203having eight antennas equally distributed about its periphery to therebydefine eight sectors 402 that together comprise the complete coveragearea 401 for this RFID-tag reader 203. (In fact, in many suchapplication settings, there can be coverage overlap between, forexample, adjacent antennas. Accordingly, if desired, the coverageinformation for such an RFID-tag reader 203 can also account foradjacent-antenna overlapping coverage areas if desired.)

The foregoing information regarding the metes and bounds of the coverageareas for each of the aforementioned RFID-tag readers 203 are thenmapped to the actual physical locations of the monitored facility. Forthe sake of an illustrative example FIG. 5 presents a simple map for afacility 500 that comprises a retail sales establishment. This facility500 includes a variety of different product displays including aplurality of shelves 501, so-called end-cap displays 502, racks 503, andfree-standing presentations 504. The aforementioned coverage information101 comprises a to-scale merger and registration of the physicallocation information of such a facility 500 with the coverage areainformation as corresponds to the various RFID-tag readers 203 at thisfacility 500.

Referring again to FIG. 2, if desired, the control circuit 201 can alsooperably couple to one or more user interfaces 204 and one or morecommunication networks 205. This user interface 204 can comprise any ofa variety of user-input mechanisms (such as, but not limited to,keyboards and keypads, cursor-control devices, touch-sensitive displays,speech-recognition interfaces, gesture-recognition interfaces, and soforth) and/or user-output mechanisms (such as, but not limited to,visual displays, audio transducers, printers, and so forth) tofacilitate receiving information and/or instructions from a user and/orproviding information to a user. The network 205, in turn, can compriseany of a variety of internal and/or external networks includingintranets and extranets (such as but not limited to the Internet).

Referring again to FIG. 1, at 102 such a control circuit 201 uses theplurality of RFID-tag readers 203 to read, over time and often manytimes, a population of RFID tags. The control circuit 201 then storeshistorical-read information as pertains to these reads.

By one approach this historical-read information includes correspondingRFID-system metrics. Examples of such metrics include but are certainlynot limited to a particular RFID-tag reader (that is, an identifier forthe particular RFID-tag reader that read the RFID tag), a particularRFID-tag reader antenna (for example, when the RFID-tag reader antennafor a given RFID-tag reader comprises a plurality of sectored antennas),a particular RFID-tag reader logical antenna (for example, when theRFID-tag reader makes use of a steerable phased antenna array), areceived signal strength indicator (RSSI) value as corresponds to theread response provided by the RFID tag when read, a received signalphase angle as corresponds to the read event, and/or a total number ofreads to note but a few examples in these regards.

This historical-read information can also include tag-specificinformation regarding each read RFID tag. This tag-specific informationcan include, for example, a unique electronic product code as specifiedby the aforementioned standard denoted as EPC Radio-Frequency IdentityProtocols Class-1 Generation-2 UHF RFID Protocol for Communications at860 MHz-960 MHz Version 1.0.9. Such an EPC code, of course, will serveto uniquely identify each RFID tag and thereby serve to distinguish readRFID tags from one another.

And, if desired, the historical-read information can also include acorresponding timestamp to denote the time at which each read occurred.The granularity of this timestamp can be as course or as fine as may bedesired. Generally speaking, for many application settings it maysuffice if the timestamp is accurate to within plus or minus 0.01seconds. In other cases it may be sufficient to simply know, forexample, the hour of the day when the read occurred.

Over time, this historical-read information will contain multiple readsfor some (but perhaps not all) of the same RFID tags. Thishistorical-read information will therefore illustrate what RFID-systemmetrics remain generally the same for a given RFID tag and which havevaried over time. As a very simple example in these regards, TABLE 1presents historical-read information as regards which of two RFID-tagreaders 203 read either of two RFID tags (i.e., RFID-tag 001 andRFID-tag 002).

TABLE 1 TAG ID READER A READER B 001 X 001 X 002 X 001 X 002 X 001 X 002X 002 X

This historical-read information reveals that, over the time period inquestion, RFID-tag 001 was read four times, each time by RFID-tag readerA, while RFID-tag 002 was also read four times, once by RFID-tag readerA and three times by RFID-tag reader B. This historical-read informationalso reveals that all three of the most recent reads for RFID-tag 002were by RFID-tag reader B. (It will be understood that this example ishighly simplified; as noted above the data items that comprise thehistorical-read information can be considerably more complete, varied,nuanced, and rich.)

At 103 the control circuit 201 uses the historical-read information ascorresponds to a given period of time of interest (such as a specifiedhour, day, week, or such other period of contiguous time as might be ofinterest in a given application setting) and the aforementioned coverageinformation 101 to determine sub-groups of the population of RFID tags.The specific nature of the sub-groups can vary as desired. For the sakeof an illustrative example it will be presumed here that the sub-groupsare defined, at least in part, by product-based categories. For example,these product-based categories can comprise Universal Product Codecategories as are known in the art (such as, but not limited to, theUPC-A which consists of 12 numerical digits that identify both themanufacturer and the generic (rather than individual) trade item).

In some cases this product categorization information may be provided bythe RFID tag itself as part of its tag-specific information. In othercases, the unique identifier provided by the RFID tag as part of itstag-specific information can be used to look-up the productcategorization as corresponds to this particular RFID tag.

More specifically, this activity at 103 serves to identify groupings ofRFID tags as correspond to given product types and the correspondingphysical locations of those product-based groupings within the facility500. By way of some very simple examples, at 103 the control circuit 201can determine that Brand ABC jeans are kept at a first physical locationin the facility 500, Brand DEF shaving cream is kept at a second,different physical location in the facility 500, and Brand GHI toastersare kept at a third, different-again physical location in the facility500.

These determinations can, of course, be more subtle in some cases. Thecontrol circuit 201 can determine, for example, that the sub-groupsinclude two different groupings of the same item, albeit at twodifferent locations. For example, one sub-group of Brand ABC jeans mightbe located on a shelf at a first physical location and a secondsub-group of Brand ABC jeans might be located in an end-cap display at asecond, different physical location. Consider, for example, thehistorical-read information presented in TABLE 2.

TABLE 2 TAG ID READER A READER B 001 95%  5% 002 93%  7% 003 25% 75% 00492%  8% 005 20% 80% 006 96%  4% 007 18% 82% 008  5% 95% 009 95%  5%

In TABLE 2, the number of reads have been aggregated for each RFID tagfor each product category (in this case, say, Brand ABC jeans) and thatinformation used to determine the percentage of reads for each RFID tagin this sub-group that were by RFID-tag reader A and that were byRFID-tag reader B. For RFID-tag 001, for example, 95% of the reads wereby RFID-tag reader A and 5% of the reads were by RFID-tag reader B. Areview of the data indicates that the RFID tags of this sub-group arelikely located at one of two physical locations, with a first physicallocation having RFID tags 001, 002, 004, 006, and 009 and with a secondphysical location having RFID tags 003, 005, 007, and 008.

In any event, to this point in the process, the control circuit hasformed sub-groupings (such as product-based sub-groupings) of the RFIDtags in the facility 500 based on, at the least, the aforementionedhistorical-read information and the coverage information 101 and thosesub-groups have been associated with specific physical locations in thefacility 500.

At 104, the control circuit 201 then uses the historical-readinformation 101 to calculate at least one aggregated RFID-system metricon a sub-group level basis for at least some of the determinedsub-groups. An example in these regards is to calculate an average valuefor a given one of the RFID-system metrics for members of the sub-group.As a very simple but illustrative example in these regards, the averagevalues for the RFID tags for the two sub-groups of Brand ABC jeansdetailed in TABLE 2 could be averaged to yield the result shown in TABLE3.

TABLE 3 SUB-GROUP READER A READER B ABC jeans sub-group 1 94.2% 5.8% ABCjeans sub-group 2   17%  83%

In effect, the control circuit 201 determines a profile comprising anaggregated view of one or more RFID-system metrics for RFID tags thatcomprise a specific sub-group. As noted above, the breadth and depth ofthese RFID-system metrics can be considerable and as a result thecorresponding profiles can be multi-faceted and multi-dimensional. And,since the sub-groups themselves are correlated to physical locationswithin the facility 500, so too are these RFID-system metrics profiles.

By one approach, the control circuit 201 can conduct and re-conduct theaforementioned actions on as frequent a basis as might be wished. Whenre-conducting the actions, the control circuit 201 can use a samesampling period as was used in previous process cycles or can usedifferent sampling periods if desired. For example, if it is known thatsignificant changes were recently made to the sales floor (for example,to accommodate some significant quantity of seasonal offerings), it maybe useful to restrict the sample period to only relatively recent reads.When significant changes to the presentation of stock have not likelyhappened, however, it can be useful to utilize relatively long sampleperiods.

These RFID-system metrics profiles can be utilized and leveraged in awide variety of ways. As but one simple illustrative example in theseregards, at 105 the control circuit 201 can optionally use the at leastone aggregated RFID-system metric to determine a location of aparticular RFID tag by comparing the at least one aggregated RFID systemmetric to read-based information regarding this particular RFID tag.

Consider, for example, an RFID tag that is read for only the very firsttime on the sales floor of the facility 500 by RFID-tag reader A. Thetag-specific information provided by the RFID tag, when read, can serveto associate this RFID tag with a particular product offering. When thatproduct offering is a pair of Brand ABC jeans, the control circuit 201can then reference, for example, the information in TABLE 3. Since thisRFID tag was read by RFID-tag reader A, the statistical likelihood isthat the RFID tag is associated with a pair of jeans that is part of theABC jeans sub-group 1 rather than the ABC jeans sub-group 2. The controlcircuit 201 can then, with a considerable degree of reliability,determine the location of this particular RFID tag to be the samelocation as the ABC jeans sub-group 1. If and as additional reads forthis particular RFID tag become available, those additional reads willprovide further data to confirm, or to correct, that conclusion.

As another example, the disclosed historical information providesmetrics that can be grouped by utilizing the aforementioned productcategorizations. Accordingly, information metrics provided by aparticular read RFID tag can be compared to the metrics for all theproduct-based sub-groups to identify when the item that corresponds tothat particular RFID tag is physically out of place as well as whereinstead that item presently resides to facilitate having an associatefind and transfer that item to its appropriate display area.

So configured, an RFID system in a given facility can readily andreliably correlate individual RFID tags with specific physical locationsnotwithstanding any specific information from the RFID tags regardingsuch locations and even when potentially lacking much of a read historyfor any particular RFID tag. That said, however, a great number ofvariables can be in play that can affect how well such an approach worksin a given application setting to reliably associate RFID tags withspecific physical locations with a facility.

For example, radio-frequency coverage is not likely to be uniform withina given facility. This lack of uniformity can be owing to any number offactors including but not limited to the shape of the facility itselfand the materials used in its construction, the shape and materialcontent of various fixtures within the facility, and local electricalinterference due to any of a variety of sources to note but a fewexamples in these regards. Similarly, RFID tags can have their readbehavior affected by the products with which they are associated. Someproducts (and/or their packaging), for example, can act as electricalshields at least to some extent. Accordingly, the ability of thedisclosed automated approach to correctly interpret historical-readinformation can vary to some extent from place to place within thefacility and/or with respect to the product sub-grouping itself.

FIG. 6 presents a process 600 to help such an automated process correctits abilities over time to correctly associate specific RFID tags withspecific physical locations within such a facility.

Pursuant to this process 600 the control circuit accesses, at 601, theaforementioned automatically-determined physical location information ascorresponds to a plurality of RFID tags within a given facility asdetermined by the aforementioned process 100. It will be recalled thatthis process 100 makes use of the aforementioned coverage information101 that maps coverage for each of a plurality of RFID-tag readers tophysical locations within the given facility as well as historical-readinformation 602 (such as, but not limited to, the aforementionedRFID-system metrics, tag-specific information, and correspondingtimestamps as correspond to RFID-tag reader reads of individual ones ofthe RFID tags) as corresponds to at least some of the RFID tags.

At 603 the control circuit also accesses supplemental informationregarding physical locations for at least some of those RFID tags. Theseteachings are highly flexible in practice and will accommodate a widevariety of types and sources of such supplemental information.

As a first example, the supplemental information can include informationregarding a floor plan-based planogram for at least part of the givenfacility. Planograms are known in the art and generally comprise visualrepresentations of a store's placement of its products or services.Planograms can assume different forms including diagrams or models thatindicate, for example, the placement of retail products on shelves. Aplanogram can reflect any of a variety of points of view including, forexample, a top plan point of view or a side-elevational point of view.Accordingly, a given planogram can indicate, for example, not only wherea given product category is displayed in terms of the facility's floorspace but where that product category resides vertically in terms ofdistance from the floor and/or with respect to other product categoriesthat may be placed above or below the product category of interest.

As a second example, the supplemental information can compriseinformation gleaned from handheld-based RFID-tag readers. For example,facility associates may use handheld RFID-tag readers from time to timeto conduct inventories of part or all of a given facility's displayedgoods. The handheld-conducted inventories can be relatively thorough andmay be able to obtain, in a single reading session, reads fromessentially all of the RFID tags for a set of items on a given shelf orthat are hanging from a given display rack. At the same time, by any ofa variety of approaches those reads can be correlated to specificshelves, racks, displays, end-caps, and/or product groupings.

In a somewhat similar manner, and as a third example, the supplementalinformation can comprise information gleaned from handheld-basedoptical-code readers such as handheld barcode readers as are very wellknown in the art. Whether an associate uses a barcode reader expresslyto develop such information for the purposes of this process 600 or forsome other reason, again, such associate-based inventorying can becorrelated by any of a variety of ways with specific locations with thefacility.

As a fourth example, the supplemental information can compriseinformation gleaned from video analytics. By one approach, for example,this information can be based upon in-facility security video camerasthat are mounted at various locations within the facility. By use, forexample, of pattern-matching algorithms of choice such video content canbe processed to identify various display infrastructure (such asshelves, racks, and so forth), various product offerings, and specificlocations within the facility. By one approach, for example, certainknown locations within the store can be marked with a visual indicatorthat such an approach can utilize as a known physical-location marker bywhich the physical location of other recognized items can be ascertainedat least to some useful extent.

And as a fifth example, the supplemental information can compriseinformation received through location reviews from customers orassociates themselves. Such information can be gathered using any of awide variety of formal and informal approaches. By one very simpleapproach, for example, a kiosk or other user interface can be providedat which an interested party can present a found, misplaced item to beread (either via an RFID-tag reader or via an optical code) and wherethis party can mark on an interactive map where they found the item.

With continued reference to FIG. 6, at 604 the control circuit thencompares the automatically-determined physical location information withthe supplemental information to identify physical-locationdiscrepancies. Such an activity can include, for example, comparingautomatically-determined physical location information for a givenRFID-tagged item with the supplemental information to identify that theRFID-tagged item was not where the automatically-determined physicallocation information had placed that item.

By one approach, discrepancies may not be identified as beingsignificant and/or of interest unless and until the identifieddiscrepancy is greater than some predetermined magnitude. For example,it may be a process requirement that a physical discrepancy be at leastthree feet in magnitude before that discrepancy will be considered ananomaly of interest for the purposes of this process 600. (Otherdistances, both shorter and longer, may provide more appropriate in agiven application setting.) To the extent that the process 600 appliessuch a threshold, these teachings will accommodate using differentthreshold distances to accommodate different circumstances. For example,different distances may apply depending upon whether the locationdiscrepancy is in a direction that is parallel to a given shelf or islateral to that same shelf.

The overall system can employ the developed information regardingdetected physical-location discrepancies as desired. By one approach,for example, a simple archival record of such discrepancies can beupdated and maintained for future study and use. By another approach,the facility's record regarding the physical location of various itemscan simply be updated to reflect corrected location information. And byanother approach, and as illustrated at 605, this process 600 canprovide for using the physical-location discrepancy information toadjust the aforementioned automated process 100 to thereby improve theaccuracy of the automated process.

Using the discrepancy information as feedback to adjust and improve theprimary process 600 can proceed in a variety of ways. By one simpleapproach, for example, this adjustment can comprise automated changes toany of a variety of algorithm parameters. The validity of such changescan then be automatically tested by continued reapplication of theprocess 600 shown in FIG. 6. By another approach, and as experience withsuch systems grows, the adjustment activity can itself implement one ormore analysis algorithms of choice that more specifically tune thefunctioning of the primary process 600 in view of the discrepancyinformation.

So configured, a statistics-based process for, amongst other things,determining the physical location of RFID tags (and their correspondingitems) can be corrected and improved over time to reflect uniquecircumstances within the corresponding facility that are otherwisedistorting the understanding of where items in the facility are located.These teachings are highly flexible in practice and will accommodate awide variety of supplemental information types, modalities, andgathering paradigms.

Those skilled in the art will recognize that a wide variety ofmodifications, alterations, and combinations can be made with respect tothe above described embodiments without departing from the scope of theinvention, and that such modifications, alterations, and combinationsare to be viewed as being within the ambit of the inventive concept.

What is claimed is:
 1. A method comprising: by a control circuit:accessing automatically-determined physical location information ascorresponds to a plurality of radio-frequency identification (RFID) tagobjects within a given facility, wherein the automatically-determinedphysical location information is automatically determined using:coverage information that maps an RFID-tag read coverage area for eachof a plurality of fixed-location RFID-tag readers to physical locationswithin the given facility; and historical-read information by theRFID-tag readers as corresponds to at least some of the RFID tags;accessing supplemental information regarding physical locations for atleast some of the RFID tags, wherein the supplemental informationcomprises: object location information received through location reviewsof the facility from customers; and comparing theautomatically-determined physical location information with thesupplemental information to thereby identify physical-locationdiscrepancies.
 2. The method of claim 1 wherein the supplementalinformation further comprises: location and inventory informationgleaned from handheld-based optical-code readers deployed in thefacility.
 3. The method of claim 1 wherein the historical-readinformation comprises, at least in part, RFID-system metrics along withtag-specific information and corresponding timestamps as correspond toRFID-tag reader reads of individual ones of at least some of the RFIDtags.
 4. The method of claim 3 wherein the RFID-system metrics includeat least one of: a particular RFID-tag reader; a particular RFID-tagreader antenna; a particular RFID-tag reader logical antenna; a receivedsignal strength indicator (RSSI) value; a received signal phase angle;and a total number of reads.
 5. The method of claim 1 wherein comparingthe automatically-determined physical location information with thesupplemental information to thereby identify physical-locationdiscrepancies comprises comparing the automatically-determined physicallocation information with the supplemental information to therebyidentify physical-location discrepancies of greater than a predeterminedmagnitude.
 6. The method of claim 5 further comprising: using thephysical-location discrepancies to adjust an automated process by whichthe automatically-determined physical location information isautomatically determined to thereby improve accuracy of the automatedprocess.
 7. The method of claim 6 wherein using the physical-locationdiscrepancies to adjust an automated process by which theautomatically-determined physical location information is automaticallydetermined comprises automatically using the physical-locationdiscrepancies to adjust an automated process by which theautomatically-determined physical location information is automaticallydetermined.
 8. An apparatus comprising: a plurality of RFID tags with agiven facility; and a control circuit configured to: accessautomatically-determined physical location information as corresponds toa plurality of radio-frequency identification (RFID) tags within a givenfacility, wherein the automatically-determined physical locationinformation is automatically determined using: coverage information thatmaps a coverage area for each of a plurality of fixed-location RFID-tagreaders to physical locations within the given facility; andhistorical-read information as corresponds to at least some of the RFIDtags; access supplemental information regarding physical locations forat least some of the RFID tags, wherein the supplemental informationcomprises: information received through location reviews from customers;and compare the automatically-determined physical location informationwith the supplemental information to thereby identify physical-locationdiscrepancies.
 9. The apparatus of claim 8 wherein the supplementalinformation further comprises: information gleaned from handheld-basedoptical-code readers.
 10. The apparatus of claim 8 wherein thehistorical-read information comprises, at least in part, RFID-systemmetrics along with tag-specific information and corresponding timestampsas correspond to RFID-tag reader reads of individual ones of at leastsome of the RFID tags.
 11. The apparatus of claim 10 wherein theRFID-system metrics include at least one of: a particular RFID-tagreader; a particular RFID-tag reader antenna; a particular RFID-tagreader logical antenna; a received signal strength indicator (RSSI)value; a received signal phase angle; and a total number of reads. 12.The apparatus of claim 8 wherein the control circuit is configured tocompare the automatically-determined physical location information withthe supplemental information to thereby identify physical-locationdiscrepancies by comparing the automatically-determined physicallocation information with the supplemental information to therebyidentify physical-location discrepancies of greater than a predeterminedmagnitude.
 13. The apparatus of claim 12 wherein the control circuit isfurther configured to automatically use the physical-locationdiscrepancies to adjust an automated process by which theautomatically-determined physical location information is automaticallydetermined to thereby improve accuracy of the automated process.